Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

IR Frequency Region: Fingerprint Region

IR Frequency Region: Fingerprint Region

IR spectra are divided into two main regions: the diagnostic region and the fingerprint region. The diagnostic region of the spectrum lies above 1500 cm−1. The absorptions resulting from single-bond vibrations of the N–H, C–H, and O–H stretch at higher wavenumbers and appear on the left side of the spectrum. The stretching absorptions of the C≡C and C≡N occur between 2100–2300 cm−1. In contrast, those arising from stretching absorptions of the C=O, C=N, and C=C occur between 1600–1850 cm−1.
The...

Veins of Upper Limbs

Veins of Upper Limbs

The human circulatory system, a marvel of biological engineering, is a complex network of vessels that transport blood throughout the body. Among these, the veins responsible for carrying blood from the upper limbs are divided into two categories: deep and superficial.
The deep venous system is primarily composed of the ulnar and radial veins. The ulnar vein, which drains the fingers through the superficial palmar venous arches, and the radial vein, which serves the palms via the deep palmar...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Hollow-core fiber gas lasers [Invited].

Light, science & applications·2026

Same author

Detection of diabetic retinopathy using multicolor image by multimodal network incorporating information bottleneck (MNIIB).

Scientific reports·2025

Same author

Tumor and Perirenal Adipose Tissue Radiomic Models for Pathological T-Stage Prediction and Biological Exploration in Clear Cell Renal Cell Carcinoma.

European journal of radiology·2025

Same author

Off-OAB: Off-Policy Policy Gradient Method With Optimal Action-Dependent Baseline.

IEEE transactions on neural networks and learning systems·2025

Same author

Comprehensive investigation of longitudinal spindle-shaped Yb-doped fibers for high-power laser applications.

Optics express·2025

Same author

Intermittent theta burst stimulation regulates microglial polarization through Cry1 to enhance neuroplasticity for stroke recovery.

Experimental neurology·2025

Same journal

RETRACTED: Zhang et al. A Novel Framework for Reconstruction and Imaging of Target Scattering Centers via Wide-Angle Incidence in Radar Networks. <i>Sensors</i> 2025, <i>25</i>, 6802.

Sensors (Basel, Switzerland)·2026

Same journal

Enhancing Unsupervised Multi-Source Domain Adaptation for Person Re-Identification via Mixture of Experts and Graph-Based Relation.

Sensors (Basel, Switzerland)·2026

Same journal

Development of an Instrumented Glove for Palmar Pressure Assessment in Kayakers.

Sensors (Basel, Switzerland)·2026

Same journal

Development and Experimental Validation of an Autonomous IoT-Based Monitoring System for Real-Time Water Quality Assessment in the Amazon River.

Sensors (Basel, Switzerland)·2026

Same journal

Semi-Supervised Adversarial Learning Framework for Controller Area Network Bus Intrusion Detection.

Sensors (Basel, Switzerland)·2026

Same journal

Smart Optimization Method for Safety Signs in Innovative Manufacturing Environments Integrating Industrial Field IoT Sensors and Knowledge Graphs.

Sensors (Basel, Switzerland)·2026

See all related articles

Search research articles

Related Experiment Video

Updated: May 8, 2026

Facial Vein Venipuncture for Murine Blood Collection

Facial Vein Venipuncture for Murine Blood Collection

Published on: September 26, 2025

Finger vein recognition with personalized feature selection.

Xiaoming Xi¹, Gongping Yang, Yilong Yin

¹School of Computer Science and Technology, Shandong University, Jinan 250101, China. fyzq10@126.com

Sensors (Basel, Switzerland)

|August 27, 2013

Summary

This summary is machine-generated.

This study introduces Pyramid Histograms of Gray, Texture and Orientation Gradients (PHGTOG) for superior finger vein biometrics. A personalized feature selection method (PFS-PHGTOG) further enhances recognition accuracy and efficiency.

More Related Videos

Capturing Dynamic Finger Gesturing with High-resolution Surface Electromyography and Computer Vision

Capturing Dynamic Finger Gesturing with High-resolution Surface Electromyography and Computer Vision

Published on: March 28, 2025

A New Best Practice for Validating Tail Vein Injections in Rat with Near-infrared-Labeled Agents

A New Best Practice for Validating Tail Vein Injections in Rat with Near-infrared-Labeled Agents

Published on: April 19, 2019

Related Experiment Videos

Last Updated: May 8, 2026

Facial Vein Venipuncture for Murine Blood Collection

Facial Vein Venipuncture for Murine Blood Collection

Published on: September 26, 2025

Capturing Dynamic Finger Gesturing with High-resolution Surface Electromyography and Computer Vision

Capturing Dynamic Finger Gesturing with High-resolution Surface Electromyography and Computer Vision

Published on: March 28, 2025

A New Best Practice for Validating Tail Vein Injections in Rat with Near-infrared-Labeled Agents

A New Best Practice for Validating Tail Vein Injections in Rat with Near-infrared-Labeled Agents

Published on: April 19, 2019

Area of Science:

Biometrics and Pattern Recognition
Computer Vision
Image Processing

Background:

Existing biometric systems face limitations in accuracy and security.
Finger vein patterns offer unique and stable biometric traits for identification.
Developing robust and efficient feature extraction methods is crucial for biometric systems.

Purpose of the Study:

To propose a novel feature extraction method for finger vein recognition.
To enhance identification performance by combining global and local image information.
To reduce computational complexity through personalized feature selection.

Main Methods:

Introduction of Pyramid Histograms of Gray, Texture and Orientation Gradients (PHGTOG) for finger vein feature extraction.
Utilizing spatial pyramid representation to capture both global and local image details.
Employing LASSO-trained sparse weight vectors for personalized feature selection (PFS-PHGTOG).

Main Results:

PHGTOG demonstrates superior performance compared to existing finger vein features.
PFS-PHGTOG further improves recognition accuracy and reduces computational load.
Experimental results validate the effectiveness of the proposed methods on dedicated databases.

Conclusions:

PHGTOG is a powerful and simple feature for finger vein recognition.
PFS-PHGTOG offers an effective approach to personalize feature selection for enhanced biometric performance.
The proposed methods represent a significant advancement in secure and efficient personal identification.